The invention relates to a method for predicting equipment performance and in particular to use of a statistical method and a model to predict an expected distribution of the equipment performance as a function of variability in input data. One method to predict equipment performance is based on applying point definitions of input values to a model. A series of point definitions are obtained representing single values for a plurality of inputs. The point definitions are applied to a model of the equipment implemented, for example, on a computer. The model generates a single-point answer representing predicted performance of the equipment.
A drawback to this method of predicting performance is that the actual performance of the equipment is more accurately a range of values based on a range of inputs. To use this process to obtain a range answers would be a sizable task. This task would involve the input values to be statistically varied, entered into the model, the model executed, the point answer written down, and then the process repeated for the next set of input data. As can be imagined, to complete this effort with acceptable resolution would take an enormous amount of time and effort.
An exemplary embodiment of the invention is directed to a method for predicting equipment performance. Input data representing an equipment parameter is obtained. The input data includes a range of values corresponding to the equipment parameter. The input data is provided to a model and a data set is generated corresponding to the model response to the input data. A set of equations is derived representing the data set. The set of equations is statistically processed to generate a probabilistic representation of equipment performance.